Motion Planning for Active Acceleration Compensation

The goal of this research is to enhance the capabilities of transport vehicles so that they can carry delicate objects of various shapes and sizes without requiring extensive packaging to protect them. This will be achieved, as first proposed by Graf and Dillmann (1997), by mounting a robotic device on top of the vehicle whose motion compensates for any forces or torques that act on the objects as a result of the vehicle’s motion, including disturbances caused by uneven terrain. This approach is called “Active Acceleration Compensation”. Several different approaches for the motion planning are implemented and compared. One degreeof-freedom motion planning algorithms include: (1) an algorithm based on optimal control theory (OCA), (2) an algorithm based on global optimization schemes (GMA), (3) a more flexible local optimization scheme based on feedback algorithms (FMPA). Finally, a three degrees-of-freedom motion planning algorithm, based on a combination of FMPA and a so called Pendulum Algorithm (3DOF-FMPA), is presented. Simulation results show that active acceleration compensation using these methods has the potential to significantly improve the performance of the system, as compared to (a) using no actuation at all; or (b) using the classic wash-out filter for motion planning.